Which integrations are available for this server?

Enables knowledge ingestion from arXiv, allowing users to search for scientific papers, ingest them into the system, and track provenance history.

How do I use PLTM MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@PLTM MCP Server search ArXiv for recent papers on AGI and check the system entropy" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

PLTM MCP Server

Procedural Long-Term Memory - An MCP server for Claude Desktop that provides 78 tools for AGI experiments based on universal principles from physics.

What This Does

Gives Claude Desktop access to:

Memory operations - Store/retrieve facts as semantic triples
Diversity retrieval - MMR, entropy injection, attention mechanisms
Meta-cognition - Self-improvement, criticality monitoring
Knowledge ingestion - ArXiv papers with real provenance
True metrics - Action accounting, efficiency tracking

Quick Start

Prerequisites

Claude Desktop
Python 3.11+

Installation

# Clone git clone https://github.com/Alby2007/pltm-mcp.git cd pltm-mcp # Install pip install -r requirements.txt # Configure Claude Desktop # Edit: %APPDATA%\Claude\claude_desktop_config.json (Windows) # or: ~/Library/Application Support/Claude/claude_desktop_config.json (Mac)

Add this to your config:

{ "mcpServers": { "pltm-memory": { "command": "python", "args": ["C:/absolute/path/to/pltm-mcp/server.py"] } } }

Restart Claude Desktop. Done!

Verify

In Claude Desktop:

Use entropy_stats to check system state

If you see metrics, it's working!

Example Usage

# Start experiment cycle start_action_cycle(cycle_id="C1") # Inject entropy to break conceptual neighborhoods inject_entropy_antipodal( user_id="alice", current_context="machine learning" ) # Retrieve with diversity mmr_retrieve( user_id="alice", query="neural networks", lambda_param=0.6 ) # Track true computational cost record_action( operation="mmr_diversity", tokens_used=450, latency_ms=180, success=True ) # Check criticality state criticality_state() # End cycle end_action_cycle() # Returns AAE efficiency

The Experiment

Hypothesis: Universal principles from physics (criticality, self-organization, emergence) can bootstrap AGI.

Current Results:

Unlocked entropy bottleneck (+56% in Cycle 21)
Measuring true computational efficiency (AAE = 0.0023)
Testing if system can self-organize toward criticality

Goal: Push system to critical point where phase transitions occur and higher-order intelligence emerges.

Tools (78 total)

Memory

store_memory_atom, retrieve_memories, update_memory, delete_memory

Diversity Retrieval

mmr_retrieve - Maximal Marginal Relevance
attention_retrieve, attention_multihead

Entropy Management

inject_entropy_antipodal - Activate distant concepts
inject_entropy_random - Sample diverse domains
inject_entropy_temporal - Mix old + recent
entropy_stats - Diagnose diversity

Meta-Cognition

self_improve_cycle - Generate/apply hypotheses
criticality_state - Check edge of chaos
criticality_recommend - Get adjustments

Action Accounting

record_action, get_aae, start_action_cycle, end_action_cycle

Knowledge Ingestion

ingest_arxiv, search_arxiv, arxiv_history

[Full tool list in server.py]

Architecture

Memory Atoms (Triples) ↓ [subject] [predicate] [object] ↓ SQLite Graph Store ↓ Retrieval Systems (Standard/MMR/Attention) ↓ Meta-Cognitive Layer (Self-improvement/Criticality) ↓ MCP Tools (78 total)

Troubleshooting

Server not connecting?

Check logs: %APPDATA%\Claude\logs\mcp-server-pltm-memory.log
Test manually: python server.py

Tools timing out?

Restart Claude Desktop after code changes

Import errors?

pip install --upgrade -r requirements.txt

Contributing

This is active research. Contributions welcome:

New entropy strategies
Better criticality metrics
Additional universal principles
Experiment protocols

License

MIT

Citation

@software{pltm2026, author = {Alby}, title = {PLTM: Procedural Long-Term Memory MCP Server}, year = {2026}, url = {https://github.com/Alby2007/pltm-mcp} }